fforbeck

[ req ]
distinguished_name="req_distinguished_name"
prompt="no"

[ req_distinguished_name ]
C="<country>"
ST="<state>"
L="1234"
O="1234"
CN="{DOMAIN}"

fforbeck

rabbitmqctl purge_queue "<target.queue>" -p <vhost>

fforbeck

#!/usr/bin/env bash
URL="http://localhost:15672/cli/rabbitmqadmin"

VHOST="<>"
USER="<>"
PWD="<>"

QUEUE="<>"
FAILED_QUEUE="<>"

fforbeck

# The command deletes the parameter after all messages are moved origin to target queue
rabbitmqctl set_parameter -p <vhost> shovel "<origin.queue.name>" '{"src-uri":"amqp://<user>:<pwd>@/<vhost_name>","src-queue":"<origin.queue.name>","dest-uri":"amqp://<user>:<pwd>@/<vhost_name>","dest-exchange":"<target.queue.name>","prefetch-count":1,"reconnect-delay":5,"add-forward-headers":false,"ack-mode":"on-confirm","delete-after":"queue-length"}'

fforbeck

##
# http://stackoverflow.com/questions/19967472/elasticsearch-unassigned-shards-how-to-fix
##
NODE="YOUR NODE NAME"
IFS=$'\n'
for line in $(curl -s 'localhost:9200/_cat/shards' | fgrep UNASSIGNED); do
  INDEX=$(echo $line | (awk '{print $1}'))
  SHARD=$(echo $line | (awk '{print $2}'))

  curl -XPOST 'localhost:9200/_cluster/reroute' -d '{

fforbeck

If you want, I can try and help with pointers as to how to improve the indexing speed you get. Its quite easy to really increase it by using some simple guidelines, for example:

- Use create in the index API (assuming you can).
- Relax the real time aspect from 1 second to something a bit higher (index.engine.robin.refresh_interval).
- Increase the indexing buffer size (indices.memory.index_buffer_size), it defaults to the value 10% which is 10% of the heap.
- Increase the number of dirty operations that trigger automatic flush (so the translog won't get really big, even though its FS based) by setting index.translog.flush_threshold (defaults to 5000).
- Increase the memory allocated to elasticsearch node. By default its 1g.
- Start with a lower replica count (even 0), and then once the bulk loading is done, increate it to the value you want it to be using the update_settings API. This will improve things as possibly less shards will be allocated to each machine.
- Increase the number of machines you have so

fforbeck

// installed Clojure packages:
// 
// * BracketHighlighter
// * lispindent
// * SublimeREPL
// * sublime-paredit

{
  "word_separators": "/\\()\"',;!@$%^&|+=[]{}`~?",
  "paredit_enabled": true,

fforbeck

{:user {:dependencies [[org.clojure/tools.namespace "0.2.3"]
                       [spyscope "0.1.3"]
                       [criterium "0.4.1"]]
        :injections [(require '(clojure.tools.namespace repl find))
                     ; try/catch to workaround an issue where `lein repl` outside a project dir
                     ; will not load reader literal definitions correctly:
                     (try (require 'spyscope.core)
                       (catch RuntimeException e))]
        :plugins [[lein-pprint "1.1.1"]
                  [lein-beanstalk "0.2.6"]

fforbeck

import static org.apache.commons.lang.StringUtils.isBlank;

import javax.servlet.http.HttpServletRequest;
import javax.servlet.http.HttpServletResponse;

import org.apache.log4j.Logger;

import net.tanesha.recaptcha.ReCaptchaImpl;
import net.tanesha.recaptcha.ReCaptchaResponse;

fforbeck

Interesse dos usuários

Versão em inglês

Motivação

Para empresas que trabalham com publicidade online, mais precisamente DSPs e suas plataformas de Real-time Bidding é muito importante coletar a analisar informações a cerca do comportamento e interesses dos usuários enquanto navegam na internet. Sendo assim, descrevo nesse graph-gist uma abordagem básica que pode ser utilizada para analisar tais dados, considerando um determinado período de tempo e os produtos visualizados por cada usuário. Vamos considerar que alguns personagens de Breaking Bad navegaram na internet há alguns dias e encontraram alguns produtos, elementos químicos e, possuem interesse em comprá-los. Tal informação será de extrema importância no momento de dar um lance em um leilão de publicidade, sabendo o perfil e interesse de um determinado usuário. Então armazenamos tais usuários, produtos e datas das visualizações para que possamos extrair essas informações futuramente.